---
dataset_info:
  features:
  - name: image
    dtype: image
  - name: label
    dtype:
      class_label:
        names:
          '0': Major Defect
          '1': Minor Defect
          '2': No Defect
  splits:
  - name: train
    num_bytes: 741149609
    num_examples: 982
  download_size: 741179545
  dataset_size: 741149609
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
license: cc-by-4.0
task_categories:
- image-classification
size_categories:
- n<1K
---
# Pomegranate Thermal Defect Classification

A dataset for classification of Pomegranate defects using thermal imagery. The dataset contains 982 images across 3 classes: Major Defect, Minor Defect, No Defect.  
Images per class:
- Major Defect: 303
- Minor Defect: 340
- No Defect: 339

This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library.

## Citation

```bibtex
@article{gaikwad2025dataset,
  title={Dataset creation of thermal images of pomegranate for internal defect detection},
  author={Gaikwad, Ashvini and Deshpande, Manoj and Bhole, Varsha},
  journal={Data in brief},
  volume={60},
  pages={111538},
  year={2025},
  publisher={Elsevier}
}
```

gaikwad, ashvini (2024), “Pomegranate Thermal Images”, Mendeley Data, V1, doi: 10.17632/djcgvgtcfm.1

*This dataset was reformatted from its original format to match HuggingFace standards.*